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The space environment is rapidly getting congested, inducing a growth of the risk of collision between Resident Space Objects (RSOs). The validity of collision risk assessment depends on the quality of the catalogs of RSOs, which shall be as accurate and up-to-date as possible. Maneuvers of operational satellites represent a problem, because, if not correctly detected and estimated, they could lead to catalog degradation or pollution. In this paper, a novel approach to tackle the maneuver detection and estimation problem is presented. The methodology, which is part of the association problem between tracks and objects, is intended to be included in real-time cataloging systems to increase their flexibility. This paper is a continuation, extension and improvement of a former work, where maneuver estimation was carried out with optical observations. The estimation algorithm is extended to radar observations with the inclusion of a new dynamical model. The joint detection and estimation scheme is tested in a simulated maintenance chain with tracks and orbits from a single satellite. In this scenario, the output of the maneuver estimation is then used as an a-priori guess in high-fidelity orbit determination, which is refined and used to compute a post-maneuver orbit. The results of the application of the detection and estimation algorithm within the simulated chain are presented, highlighting the advantages and validating the methodology, providing a basis for a wider multi-target multi-sensor association framework, with the final goal of solving the association problem with data from survey activities.